An Interactive Video Foreground Segmentation System Based on Modeling and Dynamic Graph Cut Algorithm

Article Preview

Abstract:

This paper proposes an interactive video foreground segmentation method based on modeling and graph cut algorithm. User interactions are required at initial frame or key frame of video sequence at first. Secondly we make use of user interactions information to develop background/foreground model and get foreground segmentation result of the current frame in term of graph cut algorithm. And automatic updated methods are proposed to obtain foreground segmentation results automatically on the later sequence of video without user interaction. The developed system of interactive video foreground segmentation has performances with extracting object and editing segmentation results. Experimental results on kinds of video demonstrated that our interactive segmentation system is efficient.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 532-533)

Pages:

1770-1774

Citation:

Online since:

June 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Brian L. Price, Bryan Morse, Scott Cohen. Geodesic Graph Cut for Interactive Image Segmentation, CVPR (2010).

Google Scholar

[2] BAI, X., AND SAPIRO, G. 2007. A geodesic framework for fast interactive image and video segmentation and matting. In Proc. of IEEE ICCV.

DOI: 10.21236/ada478319

Google Scholar

[3] C. Rother, V. Kolmogorov, and A. Blake. Grabcut: Interactive foreground extraction using iterated graph cuts. SIGGRAPH (2004).

DOI: 10.1145/1186562.1015720

Google Scholar

[4] Y. Li, J. Sun, C.K. Tang and H. Shum. Lazy snapping, SIGGRAPH 2004, Vol. 23, pp.303-308.

Google Scholar

[5] Y. Boykov, and M. Pi. Jolly. Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images. In Proceedings of ICCV, pages 105-112, (2001).

DOI: 10.1109/iccv.2001.937505

Google Scholar

[6] . CHUANG, Y. -Y., AGARWALA, A., CURLESS, B., SALESIN, D. H., AND SZELISKI,R. Video matting of complex scenes. In Proceedings of ACM SIGGRAPH2002, 243-248.

DOI: 10.1145/566654.566572

Google Scholar

[7] LI, Y., SUN, J., AND SHUM, H. 2005. Video object cut and paste. In Proc. ACM SIGGRAPH, 595-600.

DOI: 10.1145/1186822.1073234

Google Scholar

[8] WANG, J., BHAT, P., COLBURN, A., AGRAWALA, M., AND COHEN, M. 2005. Interactive video cutout. In Proc. of ACM SIGGRAPH.

DOI: 10.1145/1186822.1073233

Google Scholar

[9] BAI, X., Wang, J., Simon, D., AND Sapiro, G. . Video SnapCut: Robust Video Object Cutout Using Localized Classifiers, ACM SIGGRAPH 2009, 1-11.

DOI: 10.1145/1576246.1531376

Google Scholar

[10] P. Kohli and P.H.S. Torr. Efficiently solving dynamic markov random fields using graph cuts. ICCV, 2: 922-929, Oct. (2005).

DOI: 10.1109/iccv.2005.81

Google Scholar

[11] A. Criminisi, G. Cross, A. Blake, and V. Kolmogorov. Bilayersegmentation of live video. CVPR, pages 53-60, 2006.

Google Scholar

[12] Wu X., Wang,Y., Zheng, X., Monocular Video Foreground Segmentation System, ICPR (2008).

Google Scholar

[5] R.J. Ong, J.T. Dawley and P.G. Clem: submitted to Journal of Materials Research (2003).

Google Scholar